Neck circumference and the burden of metabolic syndrome disease: a population-based sample.

Background This study aims to verify the association between neck circumference (NC) and metabolic syndrome and establish NC cut-off points to predict metabolic syndrome. Methods Weight, height, NC, waist circumference, body mass index, fasting plasma glucose, HDL cholesterol, triglycerides and bloo...

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Detalles Bibliográficos
Publicado en:Journal of Public Health Vol. 44; no. 4; pp. 753 - 761
Autores principales: Zanuncio, V V, Sediyama, C M N O, Dias, M M, Nascimento, G M, Pessoa, M C, Pereira, P F, Silva, M R I, Segheto, K J, Longo, G Z
Formato: research tables/charts Journal Article
Publicado: Oxford University Press / USA Dec2022
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Background This study aims to verify the association between neck circumference (NC) and metabolic syndrome and establish NC cut-off points to predict metabolic syndrome. Methods Weight, height, NC, waist circumference, body mass index, fasting plasma glucose, HDL cholesterol, triglycerides and blood pressure were measured in a cross-sectional and population-based study with 966 adults. The association between NC and the burden of metabolic syndrome disease was evaluated by multinomial logistic regression. Receiver operating characteristic curves were used to acquire gender-specific cut-off values and predict metabolic syndrome. The NC is a simple anthropometric measurement, has low evaluation costs, can estimate the subcutaneous fat in the upper body and is related to cardiometabolic risks. Results NC is an independent predictor of metabolic syndrome burden with high association to women. The syndrome components stratification indicated that the NC of individuals with one component was lower than those with three or more (P  = 0.001). Metabolic syndrome prediction cut-off point was a NC of 39.5 cm for men and 33.3 cm for women. Conclusions Increased NC was associated with higher metabolic syndrome risks. This anthropometric parameter can be used as an additional marker for screening cardiovascular risk diseases.